A Fuzzy Linguistic IRS Model Based on a 2-Tuple Fuzzy Linguistic Approach

نویسندگان

  • Enrique Herrera-Viedma
  • Antonio Gabriel López-Herrera
  • María Luque
  • Carlos Porcel
چکیده

Information Retrieval Systems (IRSs) based on an ordinal fuzzy linguistic approach present some problems of loss of information and lack of precision when working with discrete linguistic expression domains or when applying approximation operations in the symbolic aggregation methods. In this paper, we present a new IRS model based on the 2-tuple fuzzy linguistic approach, which allows us to overcome the problems of ordinal fuzzy linguistic IRSs and improve their performance.

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عنوان ژورنال:
  • International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems

دوره 15  شماره 

صفحات  -

تاریخ انتشار 2007